PCA for two already cross-correlated time series

I have a cross-correlation matrix of the association between two human movement time series, which have originally been cross-correlated with each other in windows and with time lags. So the matrix includes windows in rows and time lags in columns.

I would like to use a feature reduction technique on this matrix within a preprocessing step of further machine learning analyses and would like to know if it is statistically valid to perform principal component analysis (PCA) on the matrix for this purpose?